Aspect-based sentiment analysis includes the machine processing of text to determine aspects (e.g., topics) that the text refers to, as well as a sentiment conveyed for aspects. Aspect extraction is an important and challenging task in aspect-based sentiment analysis. In some techniques, variants of topic models are adopted to infer aspects (topics) from text in an unsupervised setting. However, the preference for aspects semantic coherence is not directly encoded in topic models. As a result, aspects inferred by topic models can often mix loosely related aspect terms.